基于gpu的三维体绘制自适应采样

Chun-han Zhang, Hao Yin, Shanghua Xiao
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引用次数: 0

摘要

通过传统的光线投射和简单的采样和纹理映射,三维交互式体绘制是相当复杂的。由于硬件资源的限制,体绘制算法相当耗时。因此,提出了自适应采样技术来解决计算成本过高的问题。本文针对体绘制中并行光线投射算法的优化问题,提出了一种自适应采样方法,该方法主要通过非线性采样函数减少采样点数量。这种新方法在性能和渲染质量之间进行权衡时相当有效。实验结果表明,本文提出的自适应采样方法可以提高计算效率,并基于MSE和SSIM指标生成高质量的图像。
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Adaptive Sampling for GPU-based 3-D Volume Rendering
3-D interactive volume rendering can be rather complicated through conventional ray casting with simple sampling and texture mapping. Owing to the limitation of hardware resources, volume rendering algorithms are considerably time-consuming. Therefore, adaptive sampling technique is proposed to tackle the problem of excessive computational cost. In this paper, considering an optimization in parallelized ray-casting algorithms of volume rendering, we propose an adaptive sampling method, which mainly reduces the number of sampling points through non-linear sampling function. This new method can be rather effective while making a trade-off between performance and rendering quality. Our experimental results demonstrate that the proposed adaptive sampling method can result in high efficiency in computation, and produce high-quality image based on the MSE and SSIM metrics.
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